For many problem domains, overlapping variants of Schwarz solvers [1]}, [2]} have been proven to be more stable, efficient and scalable compared to nonoverlapping variants [3]}, [4]}. We utilize the concept of overlap regions by sharing additional knot spans between subdomains in order to produce better MFA reconstructions of the underlying data. This user-specified, additional overlap is described by \(\delta _j, \forall j \in [1,2]\)  in Fig. (REF ). The amount of data overlap utilized for computing the functional approximation can directly affect the conditioning in the subdomain solver, and the scalability of the overall algorithm. Additionally, we expect the residual errors \(\vec{E}\)  from the approximation to remain bounded as the number of subdomain increase with appropriate overlap regions.
